This invention relates in general to measuring instruments and in particular to measuring instruments capable of performing error analysis of the results of measurements. All measurements contain errors from sources such as background effects. These effects are typically eliminated by performing a background measurement in which no sample is present and subtracting the background result from the results of all subsequent measurements. Instrument response can also vary so that typically the results of sample measurements are normalized against the results of a reference measurement in which a reference substance is measured. In general, the normalized result is some function of the ratio between the background corrected sample result and the background corrected reference result. For example, in analysis on a spectrophotometer the normalized result is the transmittance T and is calculated from the result S of a sample measurement, the result R of a reference measurement, and the result D of a background measurement by the relation T=(S-D)/(R-D).
Normalized results such as T still contain errors due to a variety of sources. For example, in a spectrophotometer the sample and reference can vary chemically or physically, the optical source can vary in intensity, and the optical detector can vary in sensitivity. If these parameters vary significantly on a time scale which is less than the total measurement time, then these effects will produce errors in the normalized result. In addition, the sample being tested or the measurement process employed can have inherent statistical fluctuations which produce measurement error. For example, in radioactive decay processes, the number of decays per second contains an inherent fluctuation. In measurements with a spectrophotometer, the photodetectors have an inherent variation because photons striking the detector have a probability less than one of being detected and because shot noise produces variations.
In order to judge the validity of the normalized result it is necessary to know the variance of the result. In general the variance is determined by performing a series of measurements and applying well known equations to calculate the average and variance of the results of the measurements. This error analysis process has even been automated on a number of devices including several brands of pocket calculators.
So if measuring instruments are well known and automated error analysis is well known, what's spe cial about combining measurement and error analysis in one instrument? There are actually a number of benefits to combining both capabilities in a single instrument if the combination is achieved in the right manner. If the calculation process is not merged with the measurement process then an inordinately large memory would be required to hold the data from which the average and variance are calculated. In a practical sense, the amount of data is too large for separate acquisition and statistical data manipulation to be usable. This problem is especially acute in instruments, such as a spectrophotometer, which produce spectral data. Each spectral measurement actually consists of data at a large set of points. For example, if a spectrophotometer measures absorbance at 400 different wavelengths and only ten measurements are performed for each of S, R, and D, then 12,000 pieces of data must be stored for error analysis.
In order to merge the calculation process with the measurement process, the calculation process must be at least as fast as the measurement process. But to keep instrument cost down and to improve instrument speed, the central processing unit (CPU) which performs the error calculations should be available in any period in which calculations are not being performed to direct instrument control or perform non-error analysis calculations. The CPU should also control the ordering of sample, reference, and dark measurements to minimize or eliminate effects due to instrument response variation. The measurement and analysis processes also should be merged in a way which allows selection of a range of measurement integration times to enable the user to select a long enough time to reduce the variance to an acceptable level.